Improving Driver Performance and Experience in Assisted and Automated Driving With Visual Cues in the Steering Wheel

Frederik Diederichs, Arun Muthumani, Alexander Feierle, Melanie Galle, Lesley Ann Mathis, Valeria Bopp-Bertenbreiter, Harald Widlroither, Klaus Bengler

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

In automated driving it is important to ensure drivers' awareness of the currently active level of automation and to support transitions between those levels. This is possible with a suitable human-machine interface (HMI). In this driving simulator study, two visual HMI concepts (Concept A and B ) were compared with a baseline for informing drivers about three modes: manual driving, assisted driving, and automated driving. The HMIs, consisting of LED strips on the steering wheel that differed in luminance, color, and pattern, provided continuous information about the active mode and announced transitions. The assisted mode was conveyed in Concept A using a combination of amber and blue LEDs, while in Concept B only amber LEDs were used. During automated driving Concept A displayed blue LEDs and Concept B, turquoise. Both concepts were compared to a baseline HMI, with no LEDs. Thirty-eight drivers with driving licence were trained and participated. Objective measures (hands-on-wheel time, takeover time, and visual attention) are reported. Self-reported measures (mode awareness, trust, user experience, and user acceptance) from a previous publication are briefly repeated in this context (Muthumani et al.). Concept A showed 200 ms faster hands-on-wheel times than the baseline, while in Concept B several outliers were observed that prevented significance. The visual HMIs with LEDs did not influence the eyes-on-road time in any of the automation levels. Participants preferred Concept B, with more prominent differentiation between the automation levels, over Concept A.

Original languageEnglish
Pages (from-to)4843-4852
Number of pages10
JournalIEEE Transactions on Intelligent Transportation Systems
Volume23
Issue number5
DOIs
StatePublished - 1 May 2022

Keywords

  • Automated driving
  • human-machine interface
  • mode awareness
  • steering wheel
  • takeover
  • visual warning

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